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RAG in Azure with OpenAI and ChatGPT LLM model
Rating: 4.5 out of 5(585 ratings)
23,412 students

RAG in Azure with OpenAI and ChatGPT LLM model

Extending LLM models using Azure services and tools
Created byHoussem Dellai
Last updated 6/2026
English

What you'll learn

  • Understand key concepts of RAG
  • Develop practical, hands-on skills
  • Getting familiar with Azure AI tools and services
  • Extend LLM models with data

Course content

2 sections • 16 lectures • 1h 10m total length

  • Introduction6:08
  • Introduction to RAG [Presentation]8:47

    Explore retrieval augmented generation (rag) to enhance chat models by querying external data, using embeddings and vector search with Azure OpenAI, to deliver accurate, sourced answers.

  • [Demo] Creating Azure resources using the portal10:31

    Create and connect Azure AI resources using the portal to build a retrieval augmented generation workflow, including AI Studio deployments, a hub and project, and an Azure AI search service.

  • [Demo] Creating Azure resources using command line7:29

    See a hands-on demonstration of provisioning azure resources via command line, including creating resource groups, ai services, ChatGPT deployments, endpoints, keys, and a YAML connection to azure ai studio.

  • [Demo] Connecting to OpenAI ChatGPT model7:07
  • [Demo] Counting the tokens for all documents2:02
  • [Demo] Cleaning the markdown files0:51

    Demonstrates cleaning markdown content by removing links, images, and double asterisks with a Python function, preparing markdown files for LLM workflows in a RAG setup.

  • [Demo] Creating the embedding vector0:46
  • [Demo] Chunking the documents to lower the number of tokens4:48
  • [Demo] Creating Search Index in Azure AI Search2:48
  • [Demo] Uploading the chunks to AI Search1:31
  • [Demo] Searching using Vector embedding1:20

    Demonstrates writing embeddings into an Azure AI search vector index and performing a vector search to retrieve the three nearest documents, showing titles, dates, and chunk content with scores.

  • [Demo] Chatting with ChatGPT with documents2:33
  • Quiz

Requirements

  • Basic programming in Python and Notebooks
  • Basic knowledge in Azure services
  • No required knowledge in LLMs or ML

Description

Elevate your development skills with our specialized course designed for developers and IT professionals. This course focuses on the essentials of Retrieval-Augmented Generation (RAG) using Azure’s cutting-edge tools and services.

Throughout this course, you will:

  • Understand RAG Fundamentals: Learn the core principles of Retrieval-Augmented Generation and its applications.

  • Utilize Azure AI Studio: Gain hands-on experience with Azure AI Studio to build and deploy AI models.

  • Leverage LLM models like ChatGPT 4: Integrate and utilize large language models, including ChatGPT, for advanced AI solutions.

  • Embed Vectors with AI Search Service: Master the techniques of embedding vectors and enhancing search capabilities using Azure AI Search service.

  • Use RAG flow with Azure AI Studio: Create your own RAG application with few clicks from the AI Studio.

  • Use Jupiter Python notebooks: Create sample python app to perform RAG.

By the end of this course, you will have the skills to implement RAG solutions effectively, leveraging Azure’s powerful tools and services. Whether you’re looking to advance your career or enhance your technical expertise, this course provides the knowledge and practical experience you need to succeed in the rapidly evolving field of AI and machine learning.

Join us and become proficient in the latest AI technologies with Azure!

Who this course is for:

  • Beginner developers who looking for understanding and learning RAG/AI apps
  • Beginner non-developers looking for an easy way to use LLMs in their company
  • Anyone looking for creating his own Copilot

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